Paper Info
Title
A Function Principle Approach to Jaccard Ranking Fuzzy Numbers
Abstract
Ranking of fuzzy numbers plays an important role in practical use and has become a prerequisite procedure for decision-making problem in fuzzy environment. Various techniques of ranking fuzzy numbers have been developed and one of them is based on the similarity measure technique. Jaccard index similarity measure has been introduced in ranking the fuzzy numbers where the fuzzy maximum and fuzzy minimum are obtained by using the extension principle. However, this approach is only applicable to normal fuzzy numbers and therefore, fails to rank the non-normal fuzzy numbers. Besides that the extension principle does not preserve the type of membership function of the fuzzy numbers and also involves laborious mathematical operations. In this paper, a simple vertex fuzzy arithmetic operation namely function principle is applied in the Jaccard ranking index. This method is capable to rank both normal and non-normal fuzzy numbers in a simpler manner. It has also improved the ranking results by the original Jaccard ranking method and some of the existing ranking methods.
Year
DOI
Venue
2009
10.1109/SoCPaR.2009.71
SoCPaR
Keywords
Field
DocType
decision making,fuzzy set theory,Jaccard index similarity measure,Jaccard ranking fuzzy numbers,decision-making problem,function principle,similarity measure technique,vertex fuzzy arithmetic operation,Jaccard index similarity measure,extension principle,function principle,ranking fuzzy numbers
Ranking SVM,Fuzzy classification,Pattern recognition,Defuzzification,Fuzzy set operations,Fuzzy mathematics,Artificial intelligence,Fuzzy number,Type-2 fuzzy sets and systems,Membership function,Mathematics
Conference
Citations 
PageRank 
References 
1
0.37
8
Authors
2
Name
Order
Citations
PageRank
Nazirah Ramli111.39
Daud Mohamad212.40